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Inclusive Growth and Its Determinants Recent Evidence from Indonesia with Provincial Data
Desi Listyo Rini and Tulus Tahi Hamonangan Tambunan*
Center for Industry, SME and Business Competition Studies, University of Trisakti, Indonesia
Submission: February 02, 2021;Published: February 16, 2021
*Corresponding author: Tulus Tambunan, Center for Industry, SME and Business Competition Studies, University of Trisakti, Indonesia
How to cite this article:Desi L R, Tulus T H T. Inclusive Growth and Its Determinants Recent Evidence from Indonesia with Provincial Data. Ann Soc Sci Manage Stud. 2021; 6(2): 555682. DOI:10.19080/ASM.2021.06.555682
This study evaluates Indonesia’s achievement in inclusive economic growth by analyzing regional data from 34 provinces for the period 2016-2018. For this purpose, the study used three indicators of achieving inclusive economic growth, namely economic growth that reduces inequality, poverty, and unemployment (or increases employment), the Poverty-Equivalent Growth Rate (PEGR) method, and the technique of multiple linear regression analysis (i.e. the fixed effect model). The results indicate that economic growth in Indonesia is not yet fully inclusive. Only a few provinces that have achieved inclusive growth. It was found that access to technology represented by the percentage of households owning a computer and access to energy represented by the percentage of households using LPG as the main fuel for cooking have positive effects on the acceleration of inclusive economic growth in Indonesia.
According to Ali, Zhuang , Ali, Son , and Rauniyar and Kanbur , the term “inclusive economic development” has no widely accepted definition. The concept clearly encompasses inclusion and economic development, and views inclusion as a process as well as a goal. Such as Sen , Sachs , Ali, Son , Rauniyar and Kanbur , and McKinley  stress that inclusive economic development is economic growth coupled with equal economic opportunities. It focuses on creating economic opportunities and making them accessible to everyone in society at all levels, not just to the poor. In the same way, inclusive economic growth is one that emphasizes economic opportunities created by economic growth are freely available to all, particularly the poor [7,8]. Inclusive economic growth has a number of elements, which include poverty reduction, employment generation, improvement in quality of employment, agriculture development, industrial development, social sector development, reduction in regional disparities, environment protection, and equal distribution of income. Among these elements, poverty reduction, employment creation and equal distribution of income have received the most attention in empirical studies of, explicitly or implicitly, inclusive economic growth [9-15]. In Indonesia, many reforms have been carried out since the end of the 1997-98 Asian financial crisis. The government has embarked upon institutional transformation,
making the country one of the region’s most vibrant democracies.
In the social, economic, and political fields, Indonesia has seen much progress. Wide reforms have been carried out in all areas of governance, including in the financial sector, and a new development strategy has been adopted for “inclusive” economic development [7,8].
Aim and research problems
This study is part of ongoing research project on “Inclusive Development in Indonesia”. The aim of this study is to evaluate Indonesia’s achievement in inclusive economic growth by analyzing regional data from 34 provinces. The definition of inclusive economic growth used in this study is an economic growth that reduces poverty, income distribution inequality and unemployment.
This research focuses on the following three questions:
i.is Indonesia successful in achieving inclusive economic growth?
ii.Are there differences in achieving inclusive economic growth between provinces?
iii.What factors that most determine the achievement of inclusive economic growth in 34 provinces?
Until now there has not been so much research on inclusive
growth at the provincial level in Indonesia. From very few empirical
studies that the authors managed to find, there is only one study,
namely from Sholihah (2014) who conducted an empirical research
in 34 provinces for the 2008-2012 period. The result revealed that
in 2008 only a few provinces showed inclusive growth, whereas
during the 2009-2012 period none of the provinces experienced
an inclusive growth. While other studies only examined one or
a few provinces. Table 1 shows previous studies in Indonesia.
Poverty and inequality are two most important indicators in
measuring the inclusiveness of an economic growth [16-24].
So, automatically the factors that directly influence poverty and
inequality become important variables in analyzing inclusive
economic growth. These factors are (i) access to education and
healthcare [25-38]; (ii) access to capital [39-42]; (iii) employment
and business opportunities (iv) access to technology [43-50]; (vi)
access to raw materials  (vii) access to physical infrastructure
as well as non-physical infrastructure or economic infrastructure
such as information and communication technology [38,52]; (viii)
gender equity [52-55]; and (ix) access to energy . Access to
all sources of poverty reduction accelerates the achievement of
inclusive economic growth.
Theoretical framework and hypotheses
Theoretically, there are two key channels through which
economic growth affects employment and hence poverty and
inequality, namely stronger output growth and increasing labor
productivity in labor-intensive sectors [56,57]. In developing
countries including Indonesia these sectors are agriculture,
middle to low technology-based industries such as textile and
garments, footwear, leather, furniture, tobacco, electronics, and
food and beverages, and trade. However, from the literature review
it revealed that an economic growth to be inclusive is influenced
by many factors. In this study, as illustrated in Figure 1, 13 factors
are included in the analysis of inclusive growth (IG), namely
school participation rate (APS), number of community health
centers (PKM), life expectancy (AHH), regional health insurance
(JKD), credit outstanding of micro, small and medium enterprise
(MSME), percentage of households that own a computer (KMP),
percentage of households accessing the internet (INT), number
of local traditional markets (PSR), length of national roads (PES),
percentage of households that have access to proper sanitation
(SNT), percentage of households that have access to clean water
(AML), electricity (DLT), and percentage of households that use
liquified petroleum gas as main fuel for cooking (LPG) ).
Based on the theoretical framework, this research developed
two hypotheses as follows:
H1: not all provinces in Indonesia achieved inclusive growth,
H2: all determinants have a positive and significant impact on
The model and techniques of analysis used in this study differ
according to the hypothesis being tested. For H1, the analysis
model used was the Poverty-Equivalent Growth Rate (PEGR)
formula adopted from several previous similar studies conducted
by, among others, Klasen , Sholihah , Azwar , and
Prabandari . PEGR is often used to measure the benefits of
economic growth for the poor. By adopting the PEGR concept,
inclusive growth can be measured by the following formula:
IGij = inclusive growth coefficient .
Eij = growth of group i in relation to indicator j
E j = growth of indicator j .
By describing i from equation (1) as poverty (p), inequality (in)
and labor (em), and j refers to indicators of economic growth (g),
then by adopting the equation, inclusive growth can be measured
by the following formula:
a) Inclusive growth index that reduces poverty (IGp)with
the following formula:
b) Inclusive growth index that reduces inequality (IGin)with
the following formula:
c) Inclusive economic growth index in absorbing labor
(IGem)with the following formula:
IGp = inclusive growth coefficient in reducing poverty
IGem = inclusive growth coefficient in absorbing labor
Ep = poverty elasticity of average income
Epg = poverty elasticity of economic growth
Eem.g = employment elasticity of economic growth
Eem = employment elasticity of average income
Ein = inequality elasticity of average income
Eing = inequality elasticity of economic growth
Gg = economic growth.
IG index in this study is the average of the three inclusive
economic growth indices combined, so that:
An economic growth can be said to be inclusive if the value of
IG ≥ Gg
For H2, the technique of multiple linear regression analysis
was used. In this determinant analysis, the dependent variable is
inclusive growth using index values or inclusive growth coefficients
and the 13 determinants as independent variables. In a multiple
linear regression classic assumption tests were performed which
aimed to obtain the results of a regression estimate that meets
the best linear unlimited estimator requirements, which are
linear, unbiased, and minimum variables, namely, normality test,
heteroscedasticity test, autocorrelation test and multicollinearity
test. In accordance with the variables and research objectives, an
empirical linear regression regression model can be formulated
according to the inclusive growth indicator approach (the results
of the PEGR analysis), as shown by equation 6, and definition of
operational variables is given in Table 2.
This study used panel data or cross section data of 34 provinces
for 2016, 2017 and 2018 from two sources, namely Bappenas
(2018) for PKM variable, and the Central Statistics Agency (BPS,
2015a,b; 2016; 2017; 2018a,b,c; 2019a,b,c,d,e) for the remaining
independent variables. Ideally, a dynamic model over a longer
time period would be more appropriate. However, for other years,
not all provinces have data for all variables.
Since the end of the 1998 Asian financial crisis that forced the
Indonesian economy to drop sharply with a growth rate of minus
13 per cent, Indonesia’s economic growth rate has never exceeded
5.5 per cent compared to an average of 7 to 8 per cent that ever
achieved before the crisis. However, looking at the development
of the three main components of inclusive growth, it seems that
Indonesia is on the right track towards inclusive growth. As can be
seen in Figure 2, the level of inequality tends to decline; although
it is not significant and still falls into the category of moderate
inequality. Indeed, reducing inequality remains a serious problem
in Indonesia which has not been easy to overcome. This may
suggest that more government efforts are still needed to achieve
inclusive growth. The number of poor people and the level of
unemployment also shows a declining trend. Economic growth in
a region can be said to be inclusive if its inclusive growth index
(IG) is greater or equal to its economic growth (Gg). The results
show that in 2017 and 2018 IG is below the economic growth
rate although the inclusive economic index grew much faster
(39%) than the increased economic growth rate (2%) during that
period (Figure 3). This means that Indonesia’s economic growth
is not inclusive yet because only a few provinces have achieved
inclusive growth during that period. Of the 68 observations (34
provinces in 2017 and 2018), only 8 observations that achieved
inclusive growth. Meanwhile, as shown in Table 3, economic
growth, poverty, open unemployment and inequality vary by
province. To some degree, these variations reflect differences in
many growth factors between provinces including the availability
of resources, the average level of education of the workforce,
economic structure, and infrastructure development. In 2018, the
highest economic growth was achieved by Papua and West Papua
ranked second. Their high growth rates were influenced greatly
by the wealth of their natural resources, especially mining such as
copper, gold, oil and gas.
Inclusive growth index
As already explained in the metodology, in this study three
coefficients of the inclusive growth index were analyzed using
provincial data. First, the coefficient of economic growth that
reduces poverty. Economic growth is said to be inclusive if the
IGp coefficient is greater or equal to the Gg coefficient. Second,
the coefficient of economic growth that reduces inequality.
Economic growth is inclusive if the IGin coefficient is greater or
equal to the Gg coefficient. Third, the coefficient of economic
growth that increases labor absorption. Economic growth is
considered inclusive if the IGem coefficient is greater or equal to
the Gg coefficient. With respect to poverty. the results show that
in 2017 only four provinces had achieved inclusive growth and
increased to seven provinces in 2018 (Table 4). It is obvious that
most provinces in Indonesia have economic growth that is not yet
inclusive in reducing poverty. Their IGp coefficient is positive but
smaller than their Gg coefficient, meaning that poverty continued
to decrease, but only a small portion of the poor did benefit from
the growth. North Kalimantan, the newest province in Indonesia,
has negative coefficients in both years. This means that economic
growth was enjoyed by people who were not poor (anti poor). A
negative coefficient also indicates that economic growth cannot
explain its role in reducing poverty, and even tends to exacerbate
With respect inequality, in 2017 there were four provinces
that had achieved inclusive growth, i.e. Kep province. Riau, West
Nusa Tenggara, West Papua and Papua and increased in 2018 to
six provinces, i.e. Riau, Jambi, Kep. Bangka Belitung, West Java,
West Nusa Tenggara and East Kalimantan. Kep Riau, Papua and
West Papua failed to maintain their inclusive growth in 2018.
Whereas the province of West Nusa Tenggara was able to maintain
its inclusive growth in reducing inequality for two years in a row.
Regarding employment or unemployment, in 2017 there were
five provinces that have achieved inclusive growth in increasing
employment, i.e. North Sumatra, Kep. Riau, West Java, East Java
and North Kalimantan, and increased in 2018 to seven provinces,
i.e. North Sumatra, Riau, Kep. Bangka Belitung, Central Kalimantan,
East Kalimantan, Gorontalo and Maluku. Overall, the number of
provinces with inclusive growth increased between from only 2 in
2017 to 4 in 2018. North Kalimantan was the only province that
experienced a drop in IG from -1.76 in 2017 to -17.23 in 2018
This was mainly due to a significant decline of IGp from -5.44
in 2017 to -51.76 years 2018.
Next, Chow test and Hausman test were performed to
determine the panel model to be used, and the results show that
the probability value of Chi-Square is smaller than 0.05. This
means that a more appropriate model to be used to estimate the
effect of independent variables on IG is the fixed effect model. The
estimation results are as follows:
Finally, two tests were carried out, namely the individual
parameter significance test (t-test) to see whether each of these
independent variables individually affected IG significantly, and
the simultaneous significance test (F-test) to see whether all of
these independent variables together affected IG significantly
(Table 5). The results of the t-test show that there are only two
variables whose probability value is smaller than 0.05, which
means that each of them significantly affect the IG , namely the
percentage of households that own computer and the percentage
of households that use LPG as fuel for cooking. While the F-test
results show a probability value smaller than 0.05, which means
that together all these independent variables have a significant
effect on IG .
There are two important findings from this research.
First, although at the national level poverty, inequality and
unemployment continued to decline, the economic growth in
Indonesia is not yet fully inclusive. The average inclusive growth
index in Indonesia is still below the average economic growth.
Meanwhile the achievement of inclusiveness at the regional level
shows different results between provinces. However, looking
at the average index value of inclusive growth, at least during
the 2017-2018 period, IG Indonesia shows an upward trend.
In 2017 the provinces that had experienced inclusive growth
were Kep Riau and West Nusa Tenggara, and in 2018 were Kep.
Bangka Belitung, West Nusa Tenggara, East Kalimantan and Riau.
So, it can be concluded that Indonesia is well in a good track.
Second, the percentage of households that own computer that
represents households’ access to technology and the percentage
of households that use LPG gas as the main fuel for cooking that
represents their access to energy are two factors that have strong
influences in accelerating the realization of inclusive growth in
Indonesia. However, this research has some limitations which are
i) this study only used thirteen variables, i.e school participation
rate, number of Puskesmas, life expectancy, regional health
insurance, road length, number of traditional markets, number
of households that own computers, users of the Internet, access
to proper drinking water, access to proper sanitation, electricity
distribution, and the use of LPG fuel for cooking. It is most likely
that there are still many other determinants of inclusive economic
growth at the provincial level but not included in this study due to
ii) the time frame used is only 2017-2018. Ideally, a dynamic
model over a longer time period would be more appropriate.
However, for other years, not all provinces have data for all
iii) the data used is provincial data. If the study population is
regencies or cities throughout Indonesia (if data are available), the
results will be different.
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